Feedback #1

github-classroom · 2023-09-05T12:30:35Z

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Subscribed: @SyafiqahIsa @BazilahHM19 @Hilalina13 @Fiqah-Alihan

Added task 1: generating the Collatz Conjecture

added better restriction for integer.

"fixed" some parts, I hope

"fixed" some parts, part 2

haziqj

Hi, be aware of the file names you are supposed to use. There are multiple files expected for this assignment. The first one should be 01-gen_collatz.R (not solution.R).

haziqj · 2023-09-23T13:05:55Z

Congratulations on passing autograder! 🎉

Added the codes for the solutions.

Added contibution declaration

Edited the png files

19b9046 · 2023-09-26T07:03:22Z

05-open.R

This is a very informative code. Good job!

19b9046 · 2023-09-26T07:12:24Z

01-gen_collatz.R

Straight forward code to read and follow.

nichongy · 2023-09-26T07:12:53Z

Not a fan of the many notes in 5-open.R, should be in the README instead. Otherwise, well done.

Ros-2646

I think you all were very creative and for each task it is very informative. But perhaps next time when updating the codes add descriptions. I didn't quite know that there's easier way to do the codes especially for task 1 and 2 but as of the other I think you can make it shorter.

Ros-2646 · 2023-09-26T07:16:57Z

05-open.R

I really love how everything is fully explained here, but I think the actual code overwhelmed by the comments/notes/explanation.

WaqiMTC · 2023-09-26T07:34:28Z

02-eda.R

+  slice_head(n = 10) %>%
+  select(start)
+
+top10longest <- as_tibble(t(top10longest))


Ooo transposing the matrix seems like a good idea! I was wondering how you managed to create different colours for each points but I understand now!

WaqiMTC · 2023-09-26T07:42:12Z

03-backtracking.R

+    if (value == 1) {
+      break
+    }


Minor thing, but this may not be necessary, because the last term in a sequence will be 1 anyways!

mimihassan · 2023-09-26T07:43:00Z

Regarding the commit messages, it will be very helpful to write more information or details on what you have committed so it is easier for you to track the changes made

WaqiMTC · 2023-09-26T07:46:37Z

03-backtracking.R

+max_count <- function(seq, start) {
+  sum(seq > start)
+}


This isn't actually how you should count the number of backtracking in a sequence! Remember that you have to wait until a term goes below the starting number first, then count from there! This is counting immediately from the start!

WaqiMTC · 2023-09-26T07:49:14Z

03-backtracking.R

+
+max_after_backtrack <- t(max_after_backtrack)
+
+max_after_backtrack


I don't think printing this is a good idea 😅

fizahjamal

It's all great work! i really like how detailed it 😀 the only thing i'd like to comment is that explanations on the task5 r file should have been put into the readme instead, and also it would be alright to just show the outputs only on your readme file and link the rcode files. Overall, this is great work!

fizahjamal · 2023-09-26T07:45:33Z

05-open.R

oh wow! i didn't think of computing this! it's unique! but maybe the explanations would be more suitable on the readme repo instead of in this r file since essentially r file focuses mainly on writing rcodes only.

WaqiMTC · 2023-09-26T07:52:26Z

04-plots.R

+           y = length)
+) +
+  geom_point() +  
+  geom_point(data = head(backtracks_df, 10), 


I see what went wrong here! You forgot to arrange the backtracks_df by descending order of length first before using head()! So it ended up simply highlighting the first 10 rows of backtracks_df instead

Same thing happened to the other highlighted points here! You may want to validate that your plot comes out as you expected!

WaqiMTC · 2023-09-26T07:55:03Z

04-plots.R

+  scale_x_continuous(
+    limits = c(0, 2000)) +
+  scale_y_continuous(
+    limits = c(0,100))


Interesting! Yes, it is a good idea to zoom in to important points once you have shown the full plot before!

WaqiMTC · 2023-09-26T07:58:46Z

04-plots.R

+# 2) Creating a scatterplot of the highest value reached in the sequence
+
+max_after_backtrack_df <- backtracks_df %>%
+  mutate(max_val_reached = pmap_dbl(list(seq, start), max_val_reached))
+
+ggplot(data = max_after_backtrack_df,
+       aes(x = start,
+           y = max_val_reached)) +
+  geom_point() +  
+  geom_point(data = head(max_after_backtrack_df, 10),
+             aes(colour = factor(start)), 
+             size = 5) +
+  labs(
+    title = "The Highest Value Reached in the Sequence",
+    x = "Starting Integer",
+    y = "Maximum Value Reached",
+    colour = "Top 10 Starting Integer") 


It would be a good idea to use logarithmic scale for the y-axis in here, as the rest of the points are very squished together that it's difficult to see what patterns the other points might have made!

Try adding + scale_y_log10() to the bottom of this code!

WaqiMTC · 2023-09-26T08:08:22Z

05-open.R

Pretty insightful! The explanation seems to better fit for the README though! Comments are good, but too many of them makes it difficult to look at the code as a whole!

hani-hive

Overall, there are some changes that need to be corrected, but nice work everyone, and love the construction of your README.md.

hani-hive · 2023-09-26T08:04:17Z

Task4(Graph 2.1).png

Please give more information about legend and correct the plot since you've stated more than 1 colour in the legend differ from the dotted plot of black-pink.

hani-hive · 2023-09-26T08:48:44Z

06-creative.R

+       y = "Sequence Length",
+       color = "Parity") +
+
+  theme_minimal()


Nice Plot! That is another nice way of using different types of plots, that is using geom_line() to see the changes of the sequence lengths over a range of starting integers, instead of using geom_point().

WaqiMTC · 2023-09-26T09:25:01Z

06-creative.R

Really cool plot! I really appreciate how easy it is to see how even starting integer compares to odd starting integers in terms of sequence length!

WaqiMTC · 2023-09-26T09:41:48Z

Hello, well done on this repo! Here are some general issues I need to point out:

There seems to be a lack of descriptions in the commits! Please write something in your description so people can understand what has changed more quickly!
Footnotes are done by writing [^1]
There is a lack of comments inside the files! Do comment in order to let viewers of the code understand them more easily and go through the code quicker! Due to the lack of comments in most of the files, it did take a while to look through the code, hence the late submission from me 😅
It seems to me that quite a bit of the code doesn't really follow the tidyverse style guide! Admittedly, checking the tidyverse guide again and again while coding may be a bit inconvenient, so I suggest making use of the styler and lintr packages to make the style check easier!

And then personal comments:

It was really clever to use the t() function to transpose data so that each value is put into different variables, which seems like a convenient method of making the points in the plot different colours! I'm definitely stealing that idea in my future R projects, but I do suggest hiding the legend if using this method, especially if you want to highlight a large number of points!
I noticed that you included outputs inside the README, which is very nice! If you intend to do more like that, I do suggest using Rmd file format, as you can actually run code and then print the output inside the README! Of course, this seems to only work if you save and knit it in RStudio though!

Once again, great job!

mimihassan

Overall, looking at your team's simple code made me realise how much I overthink on how to code HAHA i learn a lot from your coding style, well done!

mimihassan · 2023-09-30T07:17:18Z

readme__1.md

+max_count <- function(seq, start) {
+  sum(seq > start)
+}
+
+count_df <- backtracks_df %>%
+  mutate(count=pmap_int(list(seq,start),max_count))
+
+mode_backtrack <- count_df %>%
+  group_by(count) %>%
+  summarise(seq_count = n()) %>%
+  filter(seq_count == max(seq_count)) %>%
+  pull(count)


ooh! so that's how you do it... got me all stressing for just missing one function to pass the autograde :') great work and neat coding!

mimihassan · 2023-09-30T07:24:35Z

02-eda.R

+even_odd_avg_len <- collatz_df %>%
+  group_by(parity) %>%
+  summarise(avg = mean(length)) %>%
+  arrange(avg) %>%
+  select(avg)


ooooh! your code is simple and easy to understand! that's so cool how you figure out the code and pass the autograde that fast! well done

github-classroom bot and others added 18 commits September 5, 2023 12:30

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update4

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added better restriction for integer.

Syafiqah2

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"fixed" some parts, I hope

Syafiqah3

3049f8a

"fixed" some parts, part 2

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haziqj requested changes Sep 21, 2023

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Fiqah-Alihan and others added 10 commits September 22, 2023 16:25

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SyafiqahIsa and others added 4 commits September 26, 2023 10:31

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Added the codes for the solutions.

Merge branch 'main' of https://github.com/sm2302-aug23/grp-r-fourier

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05-open.R

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This is a very informative code. Good job!

19b9046 reviewed Sep 26, 2023

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01-gen_collatz.R

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Straight forward code to read and follow.

Ros-2646 reviewed Sep 26, 2023

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05-open.R

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I really love how everything is fully explained here, but I think the actual code overwhelmed by the comments/notes/explanation.

WaqiMTC reviewed Sep 26, 2023

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03-backtracking.R

max_after_backtrack <- t(max_after_backtrack)

max_after_backtrack

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I don't think printing this is a good idea 😅

fizahjamal reviewed Sep 26, 2023

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WaqiMTC reviewed Sep 26, 2023

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hani-hive reviewed Sep 26, 2023

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mimihassan reviewed Sep 30, 2023

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		max_after_backtrack <- t(max_after_backtrack)

		max_after_backtrack

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